White et al. BMC Public Health (2015) 15:233 DOI 10.1186/s12889-015-1585-9
RESEARCH ARTICLE
Open Access
Exploring comorbid use of marijuana, tobacco, and alcohol among 14 to 15-year-olds: findings from a national survey on adolescent substance use Joanna White1*, Darren Walton1,2 and Natalie Walker3
Abstract Background: Understanding the patterns of comorbid substance use, particularly among adolescents, is necessary to address resulting harm. This study investigated the prevalence of comorbid use of marijuana, tobacco and binge drinking among 14 to 15-year-olds. The study also examined the relationship between comorbid substance use and behaviour frequency and explored common underlying risk factors for comorbid substance use. Methods: A nationally representative sample of 3,017 New Zealand Year 10 students completed self-report measures of marijuana use, tobacco use, binge drinking and socio-demographic characteristics in the 2012 Youth Insights Survey (YIS). Weighted population estimates were calculated. Ordinal logistic regression models were constructed to a) investigate the relationship between comorbidity and substance use behaviour frequency, and b) profile those with the greatest degree of comorbid substance use. Results: In the past month, one-in-twenty (4.7%) students had engaged in all three substance use behaviours, 5.8% in two, and 11.9% in one. Around half of adolescents who had engaged in one had also engaged in another, with three-quarters of tobacco-users also using marijuana and/or binge drinking. Respondents who reported a greater degree of comorbidity were likely to engage in substance use behaviour more frequently. Comorbid substance use was significantly predicted by gender, ethnicity, school decile status, past week income, social connectedness, and parental monitoring and rule enforcement. Conclusions: The results identify a core group of adolescents sharing common characteristics who frequently engage in comorbid substance use behaviours. More sophisticated and wider interventions addressing multiple substances are required, especially for marijuana and tobacco use. Keywords: Adolescence, Youth, Comorbid substance use, Marijuana, Tobacco, Alcohol
Background The harm associated with the use of marijuana, tobacco and alcohol in adolescence is substantial. For instance, marijuana appears to disrupt brain development and adolescent users of marijuana have a greater risk than adult users of developing hallucinations and psychosis [1]. Earlier onset of smoking tobacco has been shown to increase nicotine dependence and lead to heavier use and greater likelihood of continued smoking [2]. Binge drinking (i.e., consuming relatively large amounts of alcohol in a single occasion) in adolescence is associated with health risk * Correspondence: [email protected] 1 Health Promotion Agency, Wellington, New Zealand Full list of author information is available at the end of the article
behaviours such as interpersonal violence, risky sexual behaviour, attempted suicide, travelling in a car with a driver who had been drinking, as well as poor school performance [3]. In New Zealand, a sixth of school exclusions for students under the age of 16, where the student cannot return to the school and must enrol elsewhere, are due to alcohol, tobacco, or drug use [4]. In 2012, 8% of New Zealand adolescents aged 14 to 15 years were regular smokers (smoking daily, weekly, or monthly) [5], while 13% of 13 to 17-year-olds were current marijuana users and 23% had engaged in binge drinking in the past month [6].
© 2015 White et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
White et al. BMC Public Health (2015) 15:233
The use of marijuana, tobacco and alcohol tends to cluster in adolescent populations, with the use of one of these substances increasing the likelihood of the use of others [7-9]. Comorbid use of marijuana, tobacco and alcohol, where all three of these substances are used concurrently or within a short time period, is of particular concern because comorbid substance use in adolescence has been related to heavier patterns of consumption in adulthood compared with singular or dual use [10-12]. Similarly, a cross-sectional evaluation of drug use across 17 countries, including the United States and New Zealand, found that a greater number of substances used and earlier onset of use predicted later substance dependence [13]. Further evidence for the resulting harm associated with comorbid substance use in adolescence comes from studies which show that it is related to frequency of substance use. Adolescents who engage in more frequent marijuana use, tobacco use and binge drinking are at greater risk of negative outcomes such as poor mental health and school performance [12], addiction [2], and engagement in other health risk behaviours [3]. The extent to which comorbid substance use in adolescence is driven by one substance acting as a ‘gateway’ for another, or through an underlying vulnerability to substance use in general, is unclear. The Gateway Theory posits that substance use initiation follows a sequential pattern, where the use of licit substances such as tobacco or alcohol lead to future risk of using marijuana, which in turn leads to future risk of using other illicit substances [14]. A ‘reverse’ gateway effect has also been noted, where frequent marijuana use predicts future tobacco use and dependence [15]. Evidence for a common underlying vulnerability to substance use comes from associations such as those found between externalising behaviour problems and adolescent substance use [16-18]. Further, studies have found that relationships between the use of marijuana, tobacco and alcohol in adolescence could be predicted by risk factors such as parental and peer substance use [19], greater amount of weekly spending money [20] and permissive parental rules on alcohol [21]. The current study examined the patterns of comorbid marijuana use, tobacco use and binge drinking among a nationally representative sample of 14 to 15-year-old students in New Zealand. The study had three aims: 1. to identify the prevalence of comorbid substance use among New Zealand adolescents 2. to examine the relationship between the frequency of marijuana use, tobacco use and binge drinking and the comorbid combination of these behaviours 3. to profile those engaging in comorbid substance use in order to determine underlying risk factors and a common vulnerability to adolescent substance use.
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Methods Data were sourced from the 2012 New Zealand Youth Insights Survey (YIS). The YIS is a biennial survey that monitors risk and protective factors that relate to smoking uptake among adolescents. Written consent to participate was given by school principals and deputy school principals on behalf of their students. Given the anonymity of the survey and the minimal risk of harm to students it was not considered necessary to seek active consent from parents [22], although parents were advised through school newsletters that their child’s school had been invited to take part, the details of the survey, and that their child would decide whether or not to participate. Participants completed the questionnaire anonymously in a classroom setting under supervision of their teacher and a trained fieldworker. Participants were informed that their responses would remain anonymous and that participation was voluntary, and were asked to tick a box on the front of the questionnaire to indicate their consent. Participants did not put their name on the questionnaire and neither teachers nor parents were permitted to look at the questionnaires after completion. The questionnaire took on average 45 minutes to complete. Participating schools were not named or identified in any way in any publications or to the media. Ethical approval for the YIS was granted by the Ministry of Health’s multi-regional ethics committee in 2007. Participants and sampling procedure
The YIS uses a two-stage cluster sample design to obtain a nationally representative sample of New Zealand Year 10 students (predominantly 14 and 15-year-olds). A sample of 186 schools was randomly drawn from the list of all eligible schools with Year 10 students in New Zealand. Probability of school selection was proportional to roll size. One Year 10 class in each selected school was then randomly drawn from a list of all mutually exclusive Year 10 classes. Each Year 10 student had only one chance to participate and an equal opportunity of selection. All students in selected classes were invited to participate. Further detail on the YIS methodology is described in a methodology report [23]. Outcome measures
The YIS questions used for the outcome measures were aligned with other similar youth surveys [6,24]. Following the recommendation of previous research [9] this study considers substance use in the past month rather than lifetime use. Marijuana use was measured by the question, “During the past 30 days (one month), how often did you smoke marijuana (pot, grass, weed, cannabis)?” Past-month marijuana smokers were defined as students who reported they had smoked marijuana at least once in the past month. Tobacco use was measured
White et al. BMC Public Health (2015) 15:233
by the question, “During the past 30 days (one month), on how many days did you smoke cigarettes?” Past-month tobacco smokers were defined as students who reported they had smoked cigarettes on at least one day in the past month. Finally, binge drinking was measured by the question, “During the past 30 days (one month), about how often did you have 5 or more alcohol drinks in one session? (count one drink as one small glass of wine, one can or stubbie, or one ready-made alcohol drink, e.g. rum and Coke or one nip of spirits)”. Past month binge drinkers were defined as students who reported they had done this on at least one occasion in the past month. Five or more drinks in one session is the adult male limit for risk of injury recommended in low-risk alcohol drinking advice [25]. This level of drinking is therefore a conservative estimate of alcohol-related harm among this survey population. Demographic variables recorded included gender, prioritised ethnic identification (Māori or non-Māori), and school decile status (low, mid or high) as a proxy for socio-economic status. Prioritised ethnic identification allocates individuals who identify with more than one ethnic group to a single ethnic group based on whether or not they identified with Māori ethnicity [26]. School decile status was collapsed into ‘low’ (deciles 1 to 4, most deprived), ‘mid’ (deciles 5 to 7), and ‘high’ (deciles 8 to 10, least deprived). Past week income was assessed by the question, “In the past 7 days (one week), how much money did you get or earn ($ per week)?” Responses were collapsed into four categories (“none”, “$1 to $15”, “$16 to $30”, and “more than $30”a) with a roughly even proportion of respondents in each. Social connectedness was measured by combining all eight items relating to family, peer, and school connectedness (Cronbach’s alpha = 0.78), where respondents were asked the degree to which they agreed with each statement on a five-point scale ranging from “strongly agree” to “strongly disagree”. The eight items were: “I like to spend free time with my family/whānau”; “We can easily think of things to do together as a family/whānau”; “My family/whānau ask each other for help”; “I can trust my friends with personal problems”; “My friends understand and accept me for who I am”; “I feel I am treated with as much respect as other students at school/kura”; “I like going to my school/kura”; and, “I feel proud to say what school/kura I go to”. Scores were collapsed into ‘low’, ‘medium’ and ‘high’ social connectedness based around the three quartile distribution for the sample. Parental monitoring of expenditure, monitoring of whereabouts and rule enforcement were determined by agreement with three statements: “My parents or caregivers generally know what I spend my pocket money on”; “My parents or caregivers often have no idea of
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where I am, when I am away from my home” (reverse scored); and, “If I break any important rules that my parents or caregivers have set I always get into trouble”. Responses for each statement were grouped into “agree” and “disagree or don’t know”. Analysis
The sample was weighted to adjust for non-response, selection probability and to match the sample’s gender and ethnicity breakdown with the total for all New Zealand Year 10 students. Weighted population estimates were calculated for substance use behaviour prevalence and the outcome measures. Ninety-five percent confidence intervals (95% CI) were calculated using jack-knife variance estimation. Analyses were carried out using Stata IC version 12.0, and were restricted to students aged 14 to 15 years [27]. To determine whether those engaging in a greater number of substance use behaviours were likely to undertake each more frequently, three ordinal logistic regression models [28] were constructed with the dependent measure being frequency of substance use behaviour and the independent measure being whether one, two, or all three behaviours were presentb. To determine the profile of those with the greatest degree of comorbidity, all socio-demographic predictors were entered into another ordinal logistic regression model with the dependent measure being whether one, two, or all three behaviours were present.
Results Of the 186 schools selected from all New Zealand schools, 147 agreed to participate, giving a 77% school-level response rate. Completed questionnaires were received from 3,143 students, which gave a student-level response rate of 82% and an overall response rate of 65%. The analysis sample (n = 3,017) comprised 49.0% female (n = 1,435) and 22.9% people of Māori ethnicity (n = 681). In the past month, 10.1% had smoked marijuana, 11.4% had smoked tobacco, and 16.8% had engaged in binge drinking. Table 1 describes the weighted proportion frequency and prevalence estimates of the substance use behaviours in more detail. Table 2 presents the weighted proportion frequency estimates of the behaviours by socio-demographic characteristics. Prevalence of comorbid substance use behaviours
Around one-in-five students (22.4%; 95% CI = 20.3-24.6) reported engaging in at least one of the substance use behaviours in the past month. One-in-twenty (4.7%; 95% CI = 3.7-5.7) had engaged in all three, 5.8% (95% CI = 4.96.7) in two, and 11.9% (95% CI = 10.4-13.4) in one only. The prevalence of each substance use behaviour configuration was: none = 77.6% (95% CI = 75.4-79.7); only binge
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Table 1 Prevalence and frequency of substance use behaviours in the past month n
Weighted % (95% CI)
Prevalence of marijuana use in past month Smoked marijuana in past month
290
10.1 (8.7-11.5)
Did not smoke marijuana in past month
2680
89.9 (88.5-91.3)
2426
81.0 (78.8-83.1)
Frequency of marijuana use in past month Never at all
Of those who had engaged in one substance use behaviour in the past month, 46.9% had also engaged in at least one other. The weighted proportion estimates of co-occurring additional substance use behaviours are shown in Table 3. As shown, of those who had smoked tobacco in the past month, more than half (55.9%) had also smoked marijuana. A quarter (23.9%) had used tobacco in isolation, that is, without also using marijuana or binge drinking. Just under half (45.3%) of binge drinkers had not also used marijuana or tobacco.
In the past but not in the past 30 days
254
8.9 (7.5-10.3)
Once
62
2.2 (1.6-2.7)
Frequency of substance use behaviour
Two or three times
111
3.8 (3.1-4.6)
Once a week
32
1.1 (0.7-1.6)
Several times a week
37
1.3 (0.8-1.8)
Every day
17
0.5 (0.3-0.8)
Several times a day
31
1.1 (0.7-1.6)
Smoked cigarettes on at least one day in past month
335
11.4 (9.8-12.9)
The association between comorbidity and substance use behaviour frequency is presented in the ordinal regression models in Table 4. Considering the adjusted odds ratios, the results suggest that number of substance use behaviours engaged in is a significant predictor of behaviour frequency. In each instance, respondents who reported a greater number of substance use behaviours also reported undertaking each more frequently.
Did not smoke cigarettes on any days in past month
2658
88.6 (87.1-90.2)
Profile of substance use comorbidity
Prevalence of tobacco use in past month
Frequency of tobacco use in past month 0 days
2658
88.6 (87.1-90.2)
1 to 2 days
123
4.1 (3.3-4.8)
3 to 5 days
46
1.6 (1.2-2.0)
6 to 9 days
19
0.6 (0.3-0.9)
10 to 19 days
43
1.5 (1.0-2.1)
20 to 29 days
27
0.9 (0.6-1.3)
All 30 days
77
2.6 (1.9-3.4)
Binge drinking in past month
472
16.8 (15.0-18.6)
No binge drinking in past month
2421
83.2 (81.4-85.0)
2025
69.4 (67.1-71.7)
Prevalence of binge drinking in past month
Frequency of binge drinking in past month Never at all In the past but not in the past 30 days
396
13.8 (12.3-15.2)
Once
169
6.0 (5.0-7.0)
Two or three times
184
6.6 (5.5-7.6)
Once a week
62
2.2 (1.5-2.8)
Several times a week
36
1.3 (0.9-1.8)
Most days
21
0.8 (0.3-1.2)
drinking = 7.5% (95% CI = 6.3-8.7); only tobacco smoking = 2.6% (95% CI = 2.0-3.3); only marijuana smoking = 1.8% (95% CI = 1.1-2.4); binge drinking and tobacco smoking = 2.2% (95% CI = 1.6-2.8); binge drinking and marijuana smoking = 2.2% (95% CI = 1.6-2.8); tobacco and marijuana smoking = 1.4% (95% CI = 1.0-1.9); all three = 4.7% (95% CI = 3.7-5.7).
The influence of socio-demographic characteristics on degree of comorbidity is presented in the ordinal logistic regression model in Table 5. Considering the adjusted odds ratios for the selected predictor variables, the results suggest that gender, ethnicity, school decile status, past week income, social connectedness, and parental monitoring of income, monitoring of whereabouts and enforcement of rules are all significant predictors of an increasing degree of substance use comorbidity. Females were more likely to report a greater number of substance use behaviours than males. Māori ethnicity, low school decile status, higher weekly income and low social connectedness were also associated with an increasing degree of substance use comorbidity. Greater agreements that parents monitor expenditure, monitor whereabouts and enforce rules were associated with a decreasing degree of substance use comorbidity.
Discussion This is the first New Zealand study to provide data on the comorbid use of marijuana, tobacco, and binge drinking in a nationally representative sample of adolescents. The results confirm that a significant number of Year 10 students engage in substance use behaviour, with around one-in-five smoking marijuana, smoking tobacco, and/or binge drinking in the past month. Comorbid substance use was relatively common among those engaging in substance use behaviours, with around half of those engaging in one also engaging in another, and a core group of around 5% engaging in all three. The comorbid relationship between marijuana and tobacco was particularly strong, with nearly six-in-ten tobacco smokers also
White et al. BMC Public Health (2015) 15:233
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Table 2 Past month substance use behaviour by socio-demographic characteristics Smoked marijuana
Smoked tobacco
Binge drinking
n
Weighted % (95% CI)
n
Weighted % (95% CI)
n
Female
142
10.1 (8.3-12.0)
186
13.4 (11.0-15.7)
233
17.4 (14.9-19.9)
Male
148
10.1 (8.3-11.8)
149
9.5 (7.8-11.2)
239
16.2 (13.8-18.6)
Māori
153
23.0 (18.7-27.4)
147
21.7 (17.8-25.6)
198
31.3 (27.0-35.6)
Non-Māori
137
6.3 (5.1-7.6)
188
8.4 (6.9-9.8)
274
12.6 (10.7-14.5)
Low
152
17.6 (13.7-21.5)
166
18.5 (14.6-22.4)
207
24.9 (20.8-29.0)
Mid
74
7.9 (5.9-9.9)
87
9.1 (6.5-11.7)
145
16.4 (12.8-20.1)
High
64
5.8 (4.2-7.4)
82
7.4 (5.6-9.2)
120
10.6 (8.3-13.0)
More than $30
104
17.3 (13.9-20.7)
106
17.3 (13.7-20.8)
166
28.3 (24.1-32.5)
$16 to $30
93
12.0 (9.6-14.4)
106
13.4 (11.0-15.9)
146
19.8 (16.7-23.0)
$1 to $15
45
5.7 (4.1-7.4)
65
8.0 (5.9-10.1)
77
9.6 (7.4-11.9)
None
45
6.7 (5.0-8.5)
56
8.2 (6.3-10.1)
79
11.9 (9.4-14.3)
Low
115
15.4 (12.3-18.4)
130
17.1 (14.0-20.1)
168
22.4 (19.2-25.5)
Medium
80
8.0 (6.0-10.0)
91
8.8 (6.7-10.9)
158
15.9 (13.0-18.8)
High
70
6.9 (5.0-8.8)
86
8.4 (6.5-10.3)
117
12.4 (9.9-14.9)
Disagree or don’t know
163
20.9 (17.6-24.2)
177
22.6 (19.1-26.0)
215
28.1 (24.6-31.7)
Agree
121
5.8 (4.7-6.9)
151
7.0 (5.7-8.3)
252
12.4 (10.6-14.2)
Disagree or don’t know
119
22.3 (18.2-26.4)
147
27.0 (22.7-31.4)
170
32.9 (28.7-37.1)
Agree
166
7.1 (5.9-8.4)
182
7.6 (6.3-8.9)
299
13.0 (11.3-14.7)
Disagree or don’t know
108
15.8 (12.2-19.3)
113
16.0 (12.7-19.2)
176
25.2 (21.9-28.5)
Agree
177
8.1 (6.8-9.4)
215
9.8 (8.2-11.3)
293
14.0 (12.1-15.9)
Weighted % (95% CI)
Gender
Ethnicity
School decile status
Past week income
Social connectedness
Parental monitoring of expenditure
Parental monitoring of whereabouts
Parental rule enforcement
smoking marijuana. Further, those who engaged in a greater number of the substance use behaviours were likely to undertake each more frequently and therefore be at greater risk of subsequent associated harm; a finding consistent with international research [3,11,12]. The study also found common socio-demographic characteristics among those adolescents engaging in comorbid use of marijuana, tobacco, and binge drinking. Comorbid substance users were likely to be female, of Māori ethnicity, attend a low decile school, report a high past week income, have low social connectedness, and have parents who do not monitor their expenditure, monitor their whereabouts or enforce rules. These common factors are consistent with previous research [16,19-21] and support the contention that there is a common underlying vulnerability to substance use.
Given the high likelihood that adolescents engaging in one substance use behaviour will also be engaging in others, the literature recommends that public health interventions consider substance use as a whole, and that in order to effectively reach those at greatest risk interventions need to screen for, consider, and address the multiple links between substances [7,8,13,19,20,29]. However, this recommendation is only partially supported by the findings of the current study. While only a small proportion of substance-using adolescents used only tobacco or only marijuana, around half engaged in binge drinking without also using another substance, although those individuals who were binge drinking more frequently were more likely to also use the other substances. Therefore, these findings suggest that interventions targeting marijuana and tobacco use should indeed address the links with
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Table 3 Co-occurrence of additional substance use behaviours for those who smoked marijuana, smoked tobacco, or engaged in binge drinking in the past month n
Weighted % (95% CI)
Smoked marijuana Only smoked marijuana
47
17.6 (11.5-23.7)
Also smoked tobacco but did not binge drink
42
14.2 (10.1-18.2)
Also engaged in binge drinking but did not smoke tobacco
60
21.4 (15.8-27.0)
Also both smoked tobacco and engaged in binge drinking
131
46.8 (40.1-53.5)
Smoked tobacco Only smoked tobacco
77
23.9 (18.9-28.9)
Also smoked marijuana but did not binge drink
42
13.0 (9.4-16.6)
Also engaged in binge drinking but did not smoke marijuana
58
20.2 (15.5-25.0)
Also both smoked marijuana and engaged in binge drinking
131
42.9 (36.9-48.9)
Engaged in binge drinking Only engaged in binge drinking
214
45.3 (39.9-50.6)
Also smoked marijuana but did not smoke tobacco
60
13.0 (9.7-16.3)
Also smoked tobacco but did not smoke marijuana
58
13.4 (10.2-16.5)
Also both smoked marijuana and tobacco
131
Table 5 Adjusted odds ratios in the ordinal logistic regression model for socio-demographic characteristics, by degree of substance use comorbidity AOR (95% CI)
p-value
Female
1.31 (1.03-1.68)
0.031
Male
1
Gender
Ethnicity Māori
2.24 (1.72-2.92)
Non-Māori
1
RESEARCH ARTICLE
Open Access
Exploring comorbid use of marijuana, tobacco, and alcohol among 14 to 15-year-olds: findings from a national survey on adolescent substance use Joanna White1*, Darren Walton1,2 and Natalie Walker3
Abstract Background: Understanding the patterns of comorbid substance use, particularly among adolescents, is necessary to address resulting harm. This study investigated the prevalence of comorbid use of marijuana, tobacco and binge drinking among 14 to 15-year-olds. The study also examined the relationship between comorbid substance use and behaviour frequency and explored common underlying risk factors for comorbid substance use. Methods: A nationally representative sample of 3,017 New Zealand Year 10 students completed self-report measures of marijuana use, tobacco use, binge drinking and socio-demographic characteristics in the 2012 Youth Insights Survey (YIS). Weighted population estimates were calculated. Ordinal logistic regression models were constructed to a) investigate the relationship between comorbidity and substance use behaviour frequency, and b) profile those with the greatest degree of comorbid substance use. Results: In the past month, one-in-twenty (4.7%) students had engaged in all three substance use behaviours, 5.8% in two, and 11.9% in one. Around half of adolescents who had engaged in one had also engaged in another, with three-quarters of tobacco-users also using marijuana and/or binge drinking. Respondents who reported a greater degree of comorbidity were likely to engage in substance use behaviour more frequently. Comorbid substance use was significantly predicted by gender, ethnicity, school decile status, past week income, social connectedness, and parental monitoring and rule enforcement. Conclusions: The results identify a core group of adolescents sharing common characteristics who frequently engage in comorbid substance use behaviours. More sophisticated and wider interventions addressing multiple substances are required, especially for marijuana and tobacco use. Keywords: Adolescence, Youth, Comorbid substance use, Marijuana, Tobacco, Alcohol
Background The harm associated with the use of marijuana, tobacco and alcohol in adolescence is substantial. For instance, marijuana appears to disrupt brain development and adolescent users of marijuana have a greater risk than adult users of developing hallucinations and psychosis [1]. Earlier onset of smoking tobacco has been shown to increase nicotine dependence and lead to heavier use and greater likelihood of continued smoking [2]. Binge drinking (i.e., consuming relatively large amounts of alcohol in a single occasion) in adolescence is associated with health risk * Correspondence: [email protected] 1 Health Promotion Agency, Wellington, New Zealand Full list of author information is available at the end of the article
behaviours such as interpersonal violence, risky sexual behaviour, attempted suicide, travelling in a car with a driver who had been drinking, as well as poor school performance [3]. In New Zealand, a sixth of school exclusions for students under the age of 16, where the student cannot return to the school and must enrol elsewhere, are due to alcohol, tobacco, or drug use [4]. In 2012, 8% of New Zealand adolescents aged 14 to 15 years were regular smokers (smoking daily, weekly, or monthly) [5], while 13% of 13 to 17-year-olds were current marijuana users and 23% had engaged in binge drinking in the past month [6].
© 2015 White et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
White et al. BMC Public Health (2015) 15:233
The use of marijuana, tobacco and alcohol tends to cluster in adolescent populations, with the use of one of these substances increasing the likelihood of the use of others [7-9]. Comorbid use of marijuana, tobacco and alcohol, where all three of these substances are used concurrently or within a short time period, is of particular concern because comorbid substance use in adolescence has been related to heavier patterns of consumption in adulthood compared with singular or dual use [10-12]. Similarly, a cross-sectional evaluation of drug use across 17 countries, including the United States and New Zealand, found that a greater number of substances used and earlier onset of use predicted later substance dependence [13]. Further evidence for the resulting harm associated with comorbid substance use in adolescence comes from studies which show that it is related to frequency of substance use. Adolescents who engage in more frequent marijuana use, tobacco use and binge drinking are at greater risk of negative outcomes such as poor mental health and school performance [12], addiction [2], and engagement in other health risk behaviours [3]. The extent to which comorbid substance use in adolescence is driven by one substance acting as a ‘gateway’ for another, or through an underlying vulnerability to substance use in general, is unclear. The Gateway Theory posits that substance use initiation follows a sequential pattern, where the use of licit substances such as tobacco or alcohol lead to future risk of using marijuana, which in turn leads to future risk of using other illicit substances [14]. A ‘reverse’ gateway effect has also been noted, where frequent marijuana use predicts future tobacco use and dependence [15]. Evidence for a common underlying vulnerability to substance use comes from associations such as those found between externalising behaviour problems and adolescent substance use [16-18]. Further, studies have found that relationships between the use of marijuana, tobacco and alcohol in adolescence could be predicted by risk factors such as parental and peer substance use [19], greater amount of weekly spending money [20] and permissive parental rules on alcohol [21]. The current study examined the patterns of comorbid marijuana use, tobacco use and binge drinking among a nationally representative sample of 14 to 15-year-old students in New Zealand. The study had three aims: 1. to identify the prevalence of comorbid substance use among New Zealand adolescents 2. to examine the relationship between the frequency of marijuana use, tobacco use and binge drinking and the comorbid combination of these behaviours 3. to profile those engaging in comorbid substance use in order to determine underlying risk factors and a common vulnerability to adolescent substance use.
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Methods Data were sourced from the 2012 New Zealand Youth Insights Survey (YIS). The YIS is a biennial survey that monitors risk and protective factors that relate to smoking uptake among adolescents. Written consent to participate was given by school principals and deputy school principals on behalf of their students. Given the anonymity of the survey and the minimal risk of harm to students it was not considered necessary to seek active consent from parents [22], although parents were advised through school newsletters that their child’s school had been invited to take part, the details of the survey, and that their child would decide whether or not to participate. Participants completed the questionnaire anonymously in a classroom setting under supervision of their teacher and a trained fieldworker. Participants were informed that their responses would remain anonymous and that participation was voluntary, and were asked to tick a box on the front of the questionnaire to indicate their consent. Participants did not put their name on the questionnaire and neither teachers nor parents were permitted to look at the questionnaires after completion. The questionnaire took on average 45 minutes to complete. Participating schools were not named or identified in any way in any publications or to the media. Ethical approval for the YIS was granted by the Ministry of Health’s multi-regional ethics committee in 2007. Participants and sampling procedure
The YIS uses a two-stage cluster sample design to obtain a nationally representative sample of New Zealand Year 10 students (predominantly 14 and 15-year-olds). A sample of 186 schools was randomly drawn from the list of all eligible schools with Year 10 students in New Zealand. Probability of school selection was proportional to roll size. One Year 10 class in each selected school was then randomly drawn from a list of all mutually exclusive Year 10 classes. Each Year 10 student had only one chance to participate and an equal opportunity of selection. All students in selected classes were invited to participate. Further detail on the YIS methodology is described in a methodology report [23]. Outcome measures
The YIS questions used for the outcome measures were aligned with other similar youth surveys [6,24]. Following the recommendation of previous research [9] this study considers substance use in the past month rather than lifetime use. Marijuana use was measured by the question, “During the past 30 days (one month), how often did you smoke marijuana (pot, grass, weed, cannabis)?” Past-month marijuana smokers were defined as students who reported they had smoked marijuana at least once in the past month. Tobacco use was measured
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by the question, “During the past 30 days (one month), on how many days did you smoke cigarettes?” Past-month tobacco smokers were defined as students who reported they had smoked cigarettes on at least one day in the past month. Finally, binge drinking was measured by the question, “During the past 30 days (one month), about how often did you have 5 or more alcohol drinks in one session? (count one drink as one small glass of wine, one can or stubbie, or one ready-made alcohol drink, e.g. rum and Coke or one nip of spirits)”. Past month binge drinkers were defined as students who reported they had done this on at least one occasion in the past month. Five or more drinks in one session is the adult male limit for risk of injury recommended in low-risk alcohol drinking advice [25]. This level of drinking is therefore a conservative estimate of alcohol-related harm among this survey population. Demographic variables recorded included gender, prioritised ethnic identification (Māori or non-Māori), and school decile status (low, mid or high) as a proxy for socio-economic status. Prioritised ethnic identification allocates individuals who identify with more than one ethnic group to a single ethnic group based on whether or not they identified with Māori ethnicity [26]. School decile status was collapsed into ‘low’ (deciles 1 to 4, most deprived), ‘mid’ (deciles 5 to 7), and ‘high’ (deciles 8 to 10, least deprived). Past week income was assessed by the question, “In the past 7 days (one week), how much money did you get or earn ($ per week)?” Responses were collapsed into four categories (“none”, “$1 to $15”, “$16 to $30”, and “more than $30”a) with a roughly even proportion of respondents in each. Social connectedness was measured by combining all eight items relating to family, peer, and school connectedness (Cronbach’s alpha = 0.78), where respondents were asked the degree to which they agreed with each statement on a five-point scale ranging from “strongly agree” to “strongly disagree”. The eight items were: “I like to spend free time with my family/whānau”; “We can easily think of things to do together as a family/whānau”; “My family/whānau ask each other for help”; “I can trust my friends with personal problems”; “My friends understand and accept me for who I am”; “I feel I am treated with as much respect as other students at school/kura”; “I like going to my school/kura”; and, “I feel proud to say what school/kura I go to”. Scores were collapsed into ‘low’, ‘medium’ and ‘high’ social connectedness based around the three quartile distribution for the sample. Parental monitoring of expenditure, monitoring of whereabouts and rule enforcement were determined by agreement with three statements: “My parents or caregivers generally know what I spend my pocket money on”; “My parents or caregivers often have no idea of
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where I am, when I am away from my home” (reverse scored); and, “If I break any important rules that my parents or caregivers have set I always get into trouble”. Responses for each statement were grouped into “agree” and “disagree or don’t know”. Analysis
The sample was weighted to adjust for non-response, selection probability and to match the sample’s gender and ethnicity breakdown with the total for all New Zealand Year 10 students. Weighted population estimates were calculated for substance use behaviour prevalence and the outcome measures. Ninety-five percent confidence intervals (95% CI) were calculated using jack-knife variance estimation. Analyses were carried out using Stata IC version 12.0, and were restricted to students aged 14 to 15 years [27]. To determine whether those engaging in a greater number of substance use behaviours were likely to undertake each more frequently, three ordinal logistic regression models [28] were constructed with the dependent measure being frequency of substance use behaviour and the independent measure being whether one, two, or all three behaviours were presentb. To determine the profile of those with the greatest degree of comorbidity, all socio-demographic predictors were entered into another ordinal logistic regression model with the dependent measure being whether one, two, or all three behaviours were present.
Results Of the 186 schools selected from all New Zealand schools, 147 agreed to participate, giving a 77% school-level response rate. Completed questionnaires were received from 3,143 students, which gave a student-level response rate of 82% and an overall response rate of 65%. The analysis sample (n = 3,017) comprised 49.0% female (n = 1,435) and 22.9% people of Māori ethnicity (n = 681). In the past month, 10.1% had smoked marijuana, 11.4% had smoked tobacco, and 16.8% had engaged in binge drinking. Table 1 describes the weighted proportion frequency and prevalence estimates of the substance use behaviours in more detail. Table 2 presents the weighted proportion frequency estimates of the behaviours by socio-demographic characteristics. Prevalence of comorbid substance use behaviours
Around one-in-five students (22.4%; 95% CI = 20.3-24.6) reported engaging in at least one of the substance use behaviours in the past month. One-in-twenty (4.7%; 95% CI = 3.7-5.7) had engaged in all three, 5.8% (95% CI = 4.96.7) in two, and 11.9% (95% CI = 10.4-13.4) in one only. The prevalence of each substance use behaviour configuration was: none = 77.6% (95% CI = 75.4-79.7); only binge
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Table 1 Prevalence and frequency of substance use behaviours in the past month n
Weighted % (95% CI)
Prevalence of marijuana use in past month Smoked marijuana in past month
290
10.1 (8.7-11.5)
Did not smoke marijuana in past month
2680
89.9 (88.5-91.3)
2426
81.0 (78.8-83.1)
Frequency of marijuana use in past month Never at all
Of those who had engaged in one substance use behaviour in the past month, 46.9% had also engaged in at least one other. The weighted proportion estimates of co-occurring additional substance use behaviours are shown in Table 3. As shown, of those who had smoked tobacco in the past month, more than half (55.9%) had also smoked marijuana. A quarter (23.9%) had used tobacco in isolation, that is, without also using marijuana or binge drinking. Just under half (45.3%) of binge drinkers had not also used marijuana or tobacco.
In the past but not in the past 30 days
254
8.9 (7.5-10.3)
Once
62
2.2 (1.6-2.7)
Frequency of substance use behaviour
Two or three times
111
3.8 (3.1-4.6)
Once a week
32
1.1 (0.7-1.6)
Several times a week
37
1.3 (0.8-1.8)
Every day
17
0.5 (0.3-0.8)
Several times a day
31
1.1 (0.7-1.6)
Smoked cigarettes on at least one day in past month
335
11.4 (9.8-12.9)
The association between comorbidity and substance use behaviour frequency is presented in the ordinal regression models in Table 4. Considering the adjusted odds ratios, the results suggest that number of substance use behaviours engaged in is a significant predictor of behaviour frequency. In each instance, respondents who reported a greater number of substance use behaviours also reported undertaking each more frequently.
Did not smoke cigarettes on any days in past month
2658
88.6 (87.1-90.2)
Profile of substance use comorbidity
Prevalence of tobacco use in past month
Frequency of tobacco use in past month 0 days
2658
88.6 (87.1-90.2)
1 to 2 days
123
4.1 (3.3-4.8)
3 to 5 days
46
1.6 (1.2-2.0)
6 to 9 days
19
0.6 (0.3-0.9)
10 to 19 days
43
1.5 (1.0-2.1)
20 to 29 days
27
0.9 (0.6-1.3)
All 30 days
77
2.6 (1.9-3.4)
Binge drinking in past month
472
16.8 (15.0-18.6)
No binge drinking in past month
2421
83.2 (81.4-85.0)
2025
69.4 (67.1-71.7)
Prevalence of binge drinking in past month
Frequency of binge drinking in past month Never at all In the past but not in the past 30 days
396
13.8 (12.3-15.2)
Once
169
6.0 (5.0-7.0)
Two or three times
184
6.6 (5.5-7.6)
Once a week
62
2.2 (1.5-2.8)
Several times a week
36
1.3 (0.9-1.8)
Most days
21
0.8 (0.3-1.2)
drinking = 7.5% (95% CI = 6.3-8.7); only tobacco smoking = 2.6% (95% CI = 2.0-3.3); only marijuana smoking = 1.8% (95% CI = 1.1-2.4); binge drinking and tobacco smoking = 2.2% (95% CI = 1.6-2.8); binge drinking and marijuana smoking = 2.2% (95% CI = 1.6-2.8); tobacco and marijuana smoking = 1.4% (95% CI = 1.0-1.9); all three = 4.7% (95% CI = 3.7-5.7).
The influence of socio-demographic characteristics on degree of comorbidity is presented in the ordinal logistic regression model in Table 5. Considering the adjusted odds ratios for the selected predictor variables, the results suggest that gender, ethnicity, school decile status, past week income, social connectedness, and parental monitoring of income, monitoring of whereabouts and enforcement of rules are all significant predictors of an increasing degree of substance use comorbidity. Females were more likely to report a greater number of substance use behaviours than males. Māori ethnicity, low school decile status, higher weekly income and low social connectedness were also associated with an increasing degree of substance use comorbidity. Greater agreements that parents monitor expenditure, monitor whereabouts and enforce rules were associated with a decreasing degree of substance use comorbidity.
Discussion This is the first New Zealand study to provide data on the comorbid use of marijuana, tobacco, and binge drinking in a nationally representative sample of adolescents. The results confirm that a significant number of Year 10 students engage in substance use behaviour, with around one-in-five smoking marijuana, smoking tobacco, and/or binge drinking in the past month. Comorbid substance use was relatively common among those engaging in substance use behaviours, with around half of those engaging in one also engaging in another, and a core group of around 5% engaging in all three. The comorbid relationship between marijuana and tobacco was particularly strong, with nearly six-in-ten tobacco smokers also
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Table 2 Past month substance use behaviour by socio-demographic characteristics Smoked marijuana
Smoked tobacco
Binge drinking
n
Weighted % (95% CI)
n
Weighted % (95% CI)
n
Female
142
10.1 (8.3-12.0)
186
13.4 (11.0-15.7)
233
17.4 (14.9-19.9)
Male
148
10.1 (8.3-11.8)
149
9.5 (7.8-11.2)
239
16.2 (13.8-18.6)
Māori
153
23.0 (18.7-27.4)
147
21.7 (17.8-25.6)
198
31.3 (27.0-35.6)
Non-Māori
137
6.3 (5.1-7.6)
188
8.4 (6.9-9.8)
274
12.6 (10.7-14.5)
Low
152
17.6 (13.7-21.5)
166
18.5 (14.6-22.4)
207
24.9 (20.8-29.0)
Mid
74
7.9 (5.9-9.9)
87
9.1 (6.5-11.7)
145
16.4 (12.8-20.1)
High
64
5.8 (4.2-7.4)
82
7.4 (5.6-9.2)
120
10.6 (8.3-13.0)
More than $30
104
17.3 (13.9-20.7)
106
17.3 (13.7-20.8)
166
28.3 (24.1-32.5)
$16 to $30
93
12.0 (9.6-14.4)
106
13.4 (11.0-15.9)
146
19.8 (16.7-23.0)
$1 to $15
45
5.7 (4.1-7.4)
65
8.0 (5.9-10.1)
77
9.6 (7.4-11.9)
None
45
6.7 (5.0-8.5)
56
8.2 (6.3-10.1)
79
11.9 (9.4-14.3)
Low
115
15.4 (12.3-18.4)
130
17.1 (14.0-20.1)
168
22.4 (19.2-25.5)
Medium
80
8.0 (6.0-10.0)
91
8.8 (6.7-10.9)
158
15.9 (13.0-18.8)
High
70
6.9 (5.0-8.8)
86
8.4 (6.5-10.3)
117
12.4 (9.9-14.9)
Disagree or don’t know
163
20.9 (17.6-24.2)
177
22.6 (19.1-26.0)
215
28.1 (24.6-31.7)
Agree
121
5.8 (4.7-6.9)
151
7.0 (5.7-8.3)
252
12.4 (10.6-14.2)
Disagree or don’t know
119
22.3 (18.2-26.4)
147
27.0 (22.7-31.4)
170
32.9 (28.7-37.1)
Agree
166
7.1 (5.9-8.4)
182
7.6 (6.3-8.9)
299
13.0 (11.3-14.7)
Disagree or don’t know
108
15.8 (12.2-19.3)
113
16.0 (12.7-19.2)
176
25.2 (21.9-28.5)
Agree
177
8.1 (6.8-9.4)
215
9.8 (8.2-11.3)
293
14.0 (12.1-15.9)
Weighted % (95% CI)
Gender
Ethnicity
School decile status
Past week income
Social connectedness
Parental monitoring of expenditure
Parental monitoring of whereabouts
Parental rule enforcement
smoking marijuana. Further, those who engaged in a greater number of the substance use behaviours were likely to undertake each more frequently and therefore be at greater risk of subsequent associated harm; a finding consistent with international research [3,11,12]. The study also found common socio-demographic characteristics among those adolescents engaging in comorbid use of marijuana, tobacco, and binge drinking. Comorbid substance users were likely to be female, of Māori ethnicity, attend a low decile school, report a high past week income, have low social connectedness, and have parents who do not monitor their expenditure, monitor their whereabouts or enforce rules. These common factors are consistent with previous research [16,19-21] and support the contention that there is a common underlying vulnerability to substance use.
Given the high likelihood that adolescents engaging in one substance use behaviour will also be engaging in others, the literature recommends that public health interventions consider substance use as a whole, and that in order to effectively reach those at greatest risk interventions need to screen for, consider, and address the multiple links between substances [7,8,13,19,20,29]. However, this recommendation is only partially supported by the findings of the current study. While only a small proportion of substance-using adolescents used only tobacco or only marijuana, around half engaged in binge drinking without also using another substance, although those individuals who were binge drinking more frequently were more likely to also use the other substances. Therefore, these findings suggest that interventions targeting marijuana and tobacco use should indeed address the links with
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Table 3 Co-occurrence of additional substance use behaviours for those who smoked marijuana, smoked tobacco, or engaged in binge drinking in the past month n
Weighted % (95% CI)
Smoked marijuana Only smoked marijuana
47
17.6 (11.5-23.7)
Also smoked tobacco but did not binge drink
42
14.2 (10.1-18.2)
Also engaged in binge drinking but did not smoke tobacco
60
21.4 (15.8-27.0)
Also both smoked tobacco and engaged in binge drinking
131
46.8 (40.1-53.5)
Smoked tobacco Only smoked tobacco
77
23.9 (18.9-28.9)
Also smoked marijuana but did not binge drink
42
13.0 (9.4-16.6)
Also engaged in binge drinking but did not smoke marijuana
58
20.2 (15.5-25.0)
Also both smoked marijuana and engaged in binge drinking
131
42.9 (36.9-48.9)
Engaged in binge drinking Only engaged in binge drinking
214
45.3 (39.9-50.6)
Also smoked marijuana but did not smoke tobacco
60
13.0 (9.7-16.3)
Also smoked tobacco but did not smoke marijuana
58
13.4 (10.2-16.5)
Also both smoked marijuana and tobacco
131
Table 5 Adjusted odds ratios in the ordinal logistic regression model for socio-demographic characteristics, by degree of substance use comorbidity AOR (95% CI)
p-value
Female
1.31 (1.03-1.68)
0.031
Male
1
Gender
Ethnicity Māori
2.24 (1.72-2.92)
Non-Māori
1
